There are currently many avenues for users to consume media content. In addition to traditional, non-interactive avenues such as traditional television, radio, or projection screens in movie theatres, new electronic devices provide additional avenues to consume media content, such as streaming content over the Internet via computers, smart phones, or tablets. Some of these additional avenues are interactive and allow users to interact with the distributors of media content. This increased interaction allows distributors or producers of media content to provide more personalized services to the consumers of the media content.
One option for producers or distributors of media content to provide personalized services is through a recommendation engine. Such engines select new media content to recommend to the user based on information known about a user. Increasing the amount of information that a recommendation engine has concerning a specific user increases the accuracy of the recommendation engine to correctly recommend media content that the user will find interesting. As a result, gathering information concerning what media content a user finds interesting and what media content a user does not find interesting is important to providing a good user experience.
The new avenues for viewing media content allow additional interaction that allows media content distributors to more efficiently gather information relating to a user's interest. Generally, the user indicates interest in a piece of media content by selecting a level of interest or otherwise rating the media content. Many recommendation systems are integrated directly into media content display platforms and allow users to indicate whether or not they found a particular piece of media content interesting.
In addition to measuring the interest of a user or group of users, producers and distributors of media content need to measure or approximate the total number of users viewing a given piece of media content at any given time. This information is then used by producers and distributors of media content to compare the relative popularity of various pieces of media content. Relative popularity can then used to determine rates for advertisements associated with the media content.
Traditionally, total viewership data is gathered by conducting studies that sample a group of users from a population. Users record their viewership habits and that information is used to estimate total viewership statistics. These studies rely on accurate user records to provide the most accurate statistics. Other methods measure total number of downloads or the amount of data streamed. These methods rely on the user to accurately report the necessary demographic information to collect accurate and useful statistics.